IDEAS home Printed from https://ideas.repec.org/a/wly/greenh/v6y2016i6p797-811.html
   My bibliography  Save this article

Modeling of corrosion of steel tubing in CO2 storage

Author

Listed:
  • Qiang Li
  • Y. Frank Cheng

Abstract

In this work, a mechanistic model was developed to predict the corrosion rate of steel tubing under carbon storage conditions. The model integrates a number of sub‐models that quantify contributions of interrelated steps to the corrosion process. The water chemistry sub‐model determines the solution pH and the concentrations of species. The electrochemical corrosion sub‐model assesses both charge‐transfer and mass‐transfer steps and their effects on corrosion. The scale formation and its role in corrosion are considered. The finite difference method is used to solve numerical equations, and a MetLab program was written for computation of the corrosion rate. The modeling results are validated by both laboratory testing and literature data. The parametric effects, including temperature, CO2 partial pressure, solution salinity, pH, time, etc., on corrosion are predicted. The limitations of the model are also discussed. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd

Suggested Citation

  • Qiang Li & Y. Frank Cheng, 2016. "Modeling of corrosion of steel tubing in CO2 storage," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 6(6), pages 797-811, December.
    • Handle: RePEc:wly:greenh:v:6:y:2016:i:6:p:797-811
    DOI: 10.1002/ghg.1605
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ghg.1605
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ghg.1605?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Liang Zhang & Haidong Huang & Yanqing Wang & Bo Ren & Shaoran Ren & Guoli Chen & Hua Zhang, 2014. "CO 2 storage safety and leakage monitoring in the CCS demonstration project of Jilin oilfield, China," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 4(4), pages 425-439, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yanqing Wang & Liang Zhang & Shaoran Ren & Bo Ren & Bailian Chen & Jun Lu, 2020. "Identification of potential CO2 leakage pathways and mechanisms in oil reservoirs using fault tree analysis," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 10(2), pages 331-346, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:greenh:v:6:y:2016:i:6:p:797-811. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)2152-3878 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.